Comet Command-Line Utilities

When you install comet_ml, you also install a collection of utilities for the command-line interface (CLI).

  • comet upload - for uploading OfflineExperiments
  • comet optimize - for easy running of Optimizer scripts in parallel or serial
  • comet python - for injecting "import comet_ml" into your scripts
  • comet offline - for exploring offline experiment ZIP files
  • comet check - for checking and debugging your environment
  • comet models - for listing and downloading Registered Models
  • comet init - for creating example scripts from cookiecutter recipes

You can interactively get general help on these utilities with:

bash comet --help

and specific help with any of the following commands:

bash comet upload --help comet optimize --help comet python --help comet offline --help comet check --help comet models --help comet models list --help comet models download --help comet init --help

You can also easily see the comet_ml version by using:

bash comet --version

The rest of this page describes these utilities.

comet upload

The comet upload utility is used to uploading OfflineExperiments to Consider the following command line:

bash $ comet upload /tmp/comet/

This is a script that is installed when you installed comet_ml. If that fails for any reason, you can try this more direct invocation using the same Python that you used when running your script:

bash $ python -m comet_ml.scripts.comet_upload /tmp/comet/

Don’t forget to include your API Key and update the experiment path to the one displayed at the end of your OfflineExperiment script run. For more details on configuring Python, please see Comet config file.

Sending multiple offline experiments is easy. To do so, execute the same comet upload command as before, but just replace the path to your experiment like so:

bash $ comet upload /path/to/*.zip


bash $ python -m comet_ml.scripts.comet_upload /path/to/*.zip


If you encounter any bugs with either the OfflineExperiment class or uploading, please run the uploader with the following:

bash $ COMET_LOGGING_FILE_LEVEL=debug \ COMET_LOGGING_FILE=/tmp/comet.debug.log \ COMET_API_KEY=MY_API_KEY \ comet upload /path/to/experiments/*.zip


bash $ COMET_LOGGING_FILE_LEVEL=debug \ COMET_LOGGING_FILE=/tmp/comet.debug.log \ COMET_API_KEY=MY_API_KEY \ python -m comet_ml.scripts.comet_upload /path/to/experiments/*.zip

The debug logs will be in /tmp/comet.debug.log. This log will show details on all of the steps of the process. If you still have problems, please share this file with us via the Slack channel.

comet optimize

The comet optimize is a utility for running the optimizer in parallel or in serial. The format of the command line is:

bash $ comet optimize [options] [PYTHON_SCRIPT] OPTIMIZER

where OPTIMIZER is a JSON file, or an optimizer id.

PYTHON_SCRIPT is a regular Python file that takes an optimizer config file, or optimizer ID. If PYTHON_SCRIPT is not included, then an optimizer is created and the optimizer id is displayed.

Positional arguments:

  • PYTHON_SCRIPT - the name of the script to run
  • OPTIMIZER - optimizer JSON file or optimizer ID

Optional arguments:

-h, --help show this help message and exit -j PARALLEL, --parallel PARALLEL number of parallel runs -t TRIALS, --trials TRIALS number of trials per parameter configuration -e EXECUTABLE, --executable EXECUTABLE Run using an executable other than Python -d DUMP, --dump DUMP Dump the parameters to given filename

Note that comet optimize requires having your COMET_API_KEY pre-configured in one of the many ways possible, for example in an environment variable, or in your .comet.config file.

Examples of calling comet optimize:

bash $ export COMET_API_KEY=a287c4e3374d3645f3465346cc5 $ export COMET_OPTIMIZER_ID=$(comet optimize opt.json) $ comet optimize opt.json $ comet optimize -j 4 opt.json

To use an executable other than python, use -e, like so:

bash $ comet optimize -e "" opt.json

For use on machines that you want to dedicate particular GPUs per process (or similar logic), you also have access to the following environment variables:

  • COMET_OPTIMIZER_PROCESS_ID - Current job number (starting with 0, up to but not including j)
  • COMET_OPTIMIZER_PROCESS_JOBS - Total number of parallel jobs (e.g., j)

for more details, see: Comet environment variables.

For example, you could call your script as defined above:

shell $ comet optimize -j 4 optimize.json

In the script, you can access COMET_OPTIMIZER_PROCESS_ID and COMET_OPTIMIZER_PROCESS_JOBS and use particular GPU configurations:


import os

setup as per above

process_id = os.environ["COMET_OPTIMIZER_PROCESS_ID"] process_jobs = os.environ["COMET_OPTIMIZER_PROCESS_JOBS"]

Handle process_id's 0 through process_jobs - 1

if process_id == 0: # handle j == 0 elif process_id == 1: # handle j == 1 elif process_id == 2: # handle j == 2 elif process_id == 3: # handle j == 3 ```

comet python

The comet python utility is used to execute a Python script and import comet_ml automatically.

Although you still need to import comet_ml in your script, you do not need to import comet_ml before your machine learning libraries anymore.


bash comet python [-h] [-p PYTHON] [-m MODULE] python_script

Positional arguments:

  • python_script: the python script to launch

Optional arguments:

-h, --help show this help message and exit -p PYTHON, --python PYTHON Which Python interpreter to use -m MODULE, --module MODULE Run library module as a script

comet offline

The comet offline utility is used to explore offline experiment archives.


comet offline [-h] [--csv] [--section SECTION] [--level LEVEL] [--name NAME] [--output OUTPUT] [--raw-size] [--no-header] archives [archives ...]

This command line displays summaries of an offline experiments:

bash $ comet offline *.zip

You may also display the ZIP details in a CSV (Comma-Separated Value) format. This format shows an experiment's data in a row format in the following order:

  • Workspace
  • Project
  • Experiment
  • Level
  • Section
  • Name
  • Value


  • Workspace: the name of a specific workspace, or DEFAULT
  • Project: the name of a specific project, or "general"
  • Experiment: the experiment key for this experiment
  • Level: detail, maximum, or minimum
  • Section: metric, param, log_other, etc.
  • Name: name of metric, param, etc.

bash $ comet offline --csv *.zip

You may use the optional flags --level, --section, or --name to filter the rows. That is, if you use this command line:

bash $ comet offline --level detail *.zip

Note that when you use --level, --section, or --name then that implies --csv.

Positional arguments:

  • archives: the offline experiment archives to display

Optional arguments:

-h, --help show this help message and exit --csv output details in csv format --section SECTION output specific section in csv format, including param, metric, log_other, data, etc. --level LEVEL output specific summary level in csv format, including minimum, maximum, detail --name NAME output specific name in csv format, including items like loss, acc, etc. --output OUTPUT output filename for csv format --raw-size Use bytes for file sizes --no-header Use this flag to suppress CSV header

comet check

The comet check command is used to check to see if your environment is set up properly to use Comet.


comet check [-h] [--debug]

The simplest use is:

```bash $ comet check COMET INFO: ================================================================================ COMET INFO: Checking connectivity to server... COMET INFO: ================================================================================ COMET INFO: Configured server address '' COMET INFO: Server address was configured in INI file '/home/user/.comet.config' COMET INFO: Server connection is ok

COMET INFO: ================================================================================ COMET INFO: Checking connectivity to Rest API... COMET INFO: ================================================================================ COMET INFO: Configured Rest API address '' COMET INFO: Rest API address was configured in INI file '/home/user/.comet.config' COMET INFO: REST API connection is ok

COMET INFO: ================================================================================ COMET INFO: Checking connectivity to Websocket Server COMET INFO: ================================================================================ COMET WARNING: No WS address configured on client side, fallbacking on default WS address 'wss://'. If that's incorrect set the WS url through the comet.ws_url_override config key. COMET INFO: Configured WS address 'wss://' COMET INFO: Websocket connection is ok

COMET INFO: ================================================================================ COMET INFO: Checking connectivity to Optimizer Server COMET INFO: ================================================================================ COMET INFO: Configured Optimizer address '' COMET INFO: Optimizer address was configured in INI file '/home/user/.comet.config' COMET INFO: Optimizer connection is ok

COMET INFO: Summary COMET INFO: -------------------------------------------------------------------------------- COMET INFO: Server connectivity True COMET INFO: Rest API connectivity True COMET INFO: WS server connectivity True COMET INFO: Optimizer server connectivity True ```

Running with the --debug flag will provide additional details. This is quite handy for tracking down issues, especially with a new environment, or on an on-prem installation.

comet models

The comet models command is used to list and download a registered model to your local file system.


comet models download [-h] --workspace WORKSPACE --model-name MODEL_NAME (--model-version MODEL_VERSION | --model-stage MODEL_STAGE) [--output OUTPUT]


comet models list [-h] --workspace WORKSPACE

For downloading a model, you must provide the name of the workspace and the registered model name. You must also provide a specific version or stage.

For example, to download a registry model named "My Model" from the workspace "My Workspace" at version 1.0.0, you can run:

bash $ comet models download \ --workspace "My Workspace" \ --model-name "My Model" \ --model-version "1.0.0"

The registry model files will be downloaded to a directory named "model". You can choose a different output directory by using the "--output" flag.

Optional arguments:

-h, --help show this help message and exit -w WORKSPACE, --workspace WORKSPACE the workspace name of the registry model to download --model-name MODEL_NAME the name of the registry model to download --model-version MODEL_VERSION the semantic version of the registry model to download (for example: 1.0.0) --model-stage MODEL_STAGE the stage of the registry model to download (for example: production) --output OUTPUT the output directory where to download the model, default to `model`

comet init

You can use comet init to:

  1. create a Comet configuration file with your API key; OR
  2. create a new project directory with sample code based on a template

You may wish to do both in this order.

The first is used in this manner in the terminal:

$ comet init --api-key

This will ask you for your Comet API key. You can also do this progammatically. See Comet Installation for information on using comet_ml.init().

The second is used to create a new project directory with a Python script and dependency file that shows how to incorporate Comet with various ML libraries. It is called like:

$ comet init

This usage of the comet init command is used to create example scripts using the cookiecutter recipe system. It currently supports creating example scripts in python and r that can be set using the --language flag (default is python).

For example, here is an example use creating a keras example with confusion matrix, embedding visualizations, and histograms with the Comet Optimizer:

% comet init

Building Comet example script from recipe...
Please answer the following questions:
project_slug [my_project]: my_project
Select online_or_offline:
1 - Online
2 - Offline
Choose from 1, 2 [1]: 1
Select framework:
1 - keras
Choose from 1 [1]: 1
Select confusion_matrix:
1 - Yes
2 - No
Choose from 1, 2 [1]: 1
Select histogram:
1 - Yes
2 - No
Choose from 1, 2 [1]: 1
Select embedding:
1 - Yes
2 - No
Choose from 1, 2 [1]: 1
Select optimizer:
1 - No
2 - Yes
Choose from 1, 2 [1]: 2

At this point there should now be an example script in my_project/

We will continually add additional examples components to the recipe. If you have questions, or pull requests, you can make those at

Optional arguments:

optional arguments: -h, --help show this help message and exit -a, --api-key Create a ~/.config.comet file with Comet API key -l LANGUAGE, --language LANGUAGE The language of example script to generate -r, --replay Replay the last comet init -f, --force Force overwrite output directory if it exists -o OUTPUT, --output OUTPUT Output directory for scripts to go to